Navigating research ethics in health geography

The case of big data

Authored by: Nina J. Morris

Routledge Handbook of Health Geography

Print publication date:  June  2018
Online publication date:  June  2018

Print ISBN: 9781138098046
eBook ISBN: 9781315104584
Adobe ISBN:

10.4324/9781315104584-47

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Abstract

Increasingly stringent governance of professional academic conduct in recent years has seen the review of proposed studies by institutional or national Research Ethics Committees (REC) become a standard feature of health-geography research (Boden, Epstein and Latimer, 2009; Burr and Reynolds, 2010; McCormack et al., 2012). This shift, stemming from a series of 20th century biomedical research scandals (e.g., medical experimentation in 1940s Nazi Germany, the 1932–1972 Tuskegee Institute Syphilis Study in the United States) and the ethical codes published in their wake (e.g., Nuremberg Code, Declaration of Helsinki, Belmont Report) (Dyer and Demeritt, 2009; Hoeyer, Dahlager and Lynöe, 2005; Schrag, 2011), has meant that academics’ compliance with ethical standards is now a personal duty rather than simply a matter of “personal and professional integrity” (Dyer and Demeritt, 2009, p. 47). Recent interest in research ethics, however, has also been fueled by growing concerns over economic inequalities, international human rights, increasing public interest in scientific endeavors (Molyneux and Geissler, 2008) and broader social trends toward accountability (Boden, Epstein and Latimer, 2009). So, what began as an attempt to regulate medical research practice (Hammersley, 2009) has expanded to encompass “everything that might be considered ‘human subjects’ research, and […] politically extended to almost all academic research” (Emmerich, 2013, p. 177). Health geography is no exception, and in this chapter I discuss the ethical implications of research with large datasets with particular reference to issues of consent and re-identification. These issues are important not only for researchers who undertake secondary data analysis, but also for those involved in primary data collection who intend to make their data available for reuse.

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